Tomasz Nurkiewicz around Java and concurrency

Abstract Fallbacks in circuit breakers replace failure with some pre-configured response so that the scope of the malfunction is limited and hidden from the end user. However, in real life, a naïve fallback is often too simple and either confusing or unacceptable. I suggest a more robust approach to handling failures, compensating for broken transactions in the future.

Reading time: 8 minutes.

What is a circuit breaker? A circuit breaker is a layer between your code and external dependencies that have a high risk of failure. Every time you call another service, database, or even touch your own disk, there is a possibility of failure. Without circuit breakers such a simple error quickly escalates, bubbling up to your end user. All too often minor dependency brings down a huge system, resulting in 503 HTTP responses or slowness. Circuit breaker discovers raised error levels or elevated response times quickly. Rather than slowing the whole system, it cuts off entire dependency temporari…

Russian translation available: Map.merge () - метод, чтобы управлять всеми остальными

I don’t often explain a single method in JDK, but when I do, it’s about Map.merge(). Probably the most versatile operation in the key-value universe. And also rather obscure and rarely used. merge() can be explained as follows: it either puts new value under the given key (if absent) or updates existing key with a given value (UPSERT). Let’s start with the most basic example: counting unique word occurrences. Pre-Java 8 (read: pre-2014!) code was quite messy and the essence was lost in implementation details:

var map = new HashMap<String, Integer>(); words.forEach(word -> { var prev = map.get(word); if (prev == null) { map.put(word, 1); } else { map.put(word, prev + 1); } }); However, it works and for given input produces desired output:

var words = List.of("Foo", "Bar", "Foo", "Buzz", "Foo", "Buzz", &…

Martin Kleppmann, the author of Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems wrote a wonderful, comprehensive book. I consider this to be my most valuable reading of 2018, even though the book is almost 2 years old now. Martin proves that great bestsellers in the programming industry aren’t about shiny new frameworks and buzzwords. Data-Intensive Applications is a solid piece about the fundamentals of computer systems, especially from the data manipulation perspective.

This book introduces and explains all topics related to data storage, retrieval and transmission. That doesn’t sound very exciting, does it? However, expect very thorough (600+ pages!) and enjoyable journey through databases, protocols, algorithms and distributed systems.

In the first chapter: “Reliable, Scalable, and Maintainable Applications” the author describes the environment in which our systems live nowadays. What are the possible failure modes (softwar…

Summary:Stick to whichever library you already have on your CLASSPATH.If you get a choice, Reactor is preferable, RxJava 2.x is still a good alternativeIn case you’re on Android, then RxJava 2.x is your only choice Table of contents:APIType-safetyChecked exceptionsTestingDebuggingSpring supportAndroid developmentMaturitySummary Many people ask me, which library to use in their new projects (if any). Some are concerned that they learned RxJava 1.x and then 2.x came along, and the Reactor. Which one should they use? And some also wonder, what’s with this new java.util.concurrent.Flow? Let me clarify a few things. First of all, both versions of RxJava and Reactor are quite similar from a functional perspective. If you know 1.x or 2.x, Reactor will be very familiar, though you still have to learn about the differences. Secondly, Flow class (a set of interfaces, to be precise) is part of a reactive streams specification, bundled into JDK. This specification dictates that various reactive …